
Call:
lm_robust(formula = scale10 ~ treatment, data = data)

Standard error type:  HC2 

Coefficients:
            Estimate Std. Error t value                                      Pr(>|t|) CI Lower CI Upper
(Intercept)  0.59630    0.03474  17.166 0.0000000000000000000000000000000000000005593 0.527759   0.6648
treatment    0.09493    0.04510   2.105 0.0366584627483656222413088698885985650122166 0.005951   0.1839
             DF
(Intercept) 183
treatment   183

Multiple R-squared:  0.02384 ,	Adjusted R-squared:  0.01851 
F-statistic: 4.431 on 1 and 183 DF,  p-value: 0.03666

Call:
lm_robust(formula = scale98 ~ treatment, data = data)

Standard error type:  HC2 

Coefficients:
            Estimate Std. Error t value                                       Pr(>|t|) CI Lower
(Intercept)   0.6407    0.03620  17.701 0.00000000000000000000000000000000000000001657   0.5693
treatment    -0.1250    0.05266  -2.373 0.01868310525332012375643309098904865095391870  -0.2288
            CI Upper  DF
(Intercept)  0.71216 183
treatment   -0.02106 183

Multiple R-squared:  0.02972 ,	Adjusted R-squared:  0.02442 
F-statistic: 5.631 on 1 and 183 DF,  p-value: 0.01868

Call:
lm_robust(formula = scale96 ~ treatment, data = data)

Standard error type:  HC2 

Coefficients:
            Estimate Std. Error t value                                      Pr(>|t|) CI Lower CI Upper
(Intercept)  0.61481    0.03490  17.615 0.0000000000000000000000000000000000000000292    0.546  0.68368
treatment   -0.08499    0.05219  -1.629 0.1051338022651109871397068218357162550091743   -0.188  0.01798
             DF
(Intercept) 183
treatment   183

Multiple R-squared:  0.01418 ,	Adjusted R-squared:  0.008798 
F-statistic: 2.652 on 1 and 183 DF,  p-value: 0.1051

Call:
lm_robust(formula = scale94 ~ treatment, data = data)

Standard error type:  HC2 

Coefficients:
            Estimate Std. Error t value                                 Pr(>|t|) CI Lower CI Upper  DF
(Intercept)  0.59074    0.03827  15.436 0.00000000000000000000000000000000005731   0.5152  0.66625 183
treatment   -0.06092    0.05585  -1.091 0.27683886496858206571758387326553929597  -0.1711  0.04928 183

Multiple R-squared:  0.006428 ,	Adjusted R-squared:  0.0009988 
F-statistic:  1.19 on 1 and 183 DF,  p-value: 0.2768

Call:
lm_robust(formula = scale92 ~ treatment, data = data)

Standard error type:  HC2 

Coefficients:
            Estimate Std. Error t value                               Pr(>|t|) CI Lower CI Upper  DF
(Intercept)   0.5852    0.03926  14.905 0.000000000000000000000000000000002067   0.5077  0.66265 183
treatment    -0.1255    0.05422  -2.315 0.021697244940110344685324506031065539  -0.2325 -0.01857 183

Multiple R-squared:  0.0285 ,	Adjusted R-squared:  0.02319 
F-statistic: 5.361 on 1 and 183 DF,  p-value: 0.0217

Call:
lm_robust(formula = scale90 ~ treatment, data = data)

Standard error type:  HC2 

Coefficients:
            Estimate Std. Error t value                        Pr(>|t|) CI Lower CI Upper  DF
(Intercept)  0.47963    0.03806  12.603 0.00000000000000000000000001273   0.4045  0.55472 183
treatment   -0.03752    0.05300  -0.708 0.47987223595788131014217015036  -0.1421  0.06705 183

Multiple R-squared:  0.002732 ,	Adjusted R-squared:  -0.002718 
F-statistic: 0.5012 on 1 and 183 DF,  p-value: 0.4799
    Policy        Condition     Mean Ci_lower Ci_upper NA
1     0 TL Women Candidates 59.62963 52.82115 66.43811 NA
2     0 TL   Men Candidates 69.12281 60.28345 77.96216 NA
3   200 TL Women Candidates 64.07407 56.97940 71.16875 NA
4   200 TL   Men Candidates 51.57895 41.25830 61.89959 NA
5   400 TL Women Candidates 61.48148 54.64046 68.32250 NA
6   400 TL   Men Candidates 52.98246 42.75352 63.21140 NA
7   600 TL Women Candidates 59.07407 51.57322 66.57493 NA
8   600 TL   Men Candidates 52.98246 42.03575 63.92916 NA
9   800 TL Women Candidates 58.51852 50.82333 66.21370 NA
10  800 TL   Men Candidates 45.96491 35.33845 56.59138 NA
11 1000 TL Women Candidates 47.96296 40.50367 55.42226 NA
12 1000 TL   Men Candidates 44.21053 33.82181 54.59925 NA
   Policy        ITT    Ci_lower  Ci_upper NA
1    0 TL   9.493177   0.5951401 18.391215 NA
2  200 TL -12.495127 -22.8842882 -2.105965 NA
3  400 TL  -8.499026 -18.7958725  1.797821 NA
4  600 TL  -6.091618 -17.1109931  4.927758 NA
5  800 TL -12.553606 -23.2506159 -1.856596 NA
6 1000 TL  -3.752437 -14.2101264  6.705253 NA
     CandidateGender       ITT   Ci_lower  Ci_upper                Ratings NA
1     1. Full sample  5.135135  0.9214953  9.348774 Trustworhiness ratings NA
2     1. Full sample  9.429429  5.2587277 13.600131     Competence ratings NA
3 3. Woman candidate  5.972222 -0.1869750 12.131419 Trustworhiness ratings NA
4 3. Woman candidate 12.839506  6.4894243 19.189588     Competence ratings NA
5   2. Man candidate  4.342105 -1.3229962 10.007206 Trustworhiness ratings NA
6   2. Man candidate  6.198830  0.8237553 11.573905     Competence ratings NA
       RespondentGender        ITT    Ci_lower   Ci_upper Policy NA
1        1. Full sample   9.493177   0.5951401 18.3912148   0 TL NA
2        1. Full sample -12.495127 -22.8842882 -2.1059654 200 TL NA
3 2. Women participants  -3.751803 -19.3885952 11.8849883   0 TL NA
4 2. Women participants -17.431457 -34.0556673 -0.8072476 200 TL NA
5   3. Men participants  18.264411   7.5837633 28.9450587   0 TL NA
6   3. Men participants  -8.458647 -21.9893212  5.0720279 200 TL NA

 1  2  3  4 
44 46 47 48 
\begin{table}

\caption{Descriptive Statistics}
\centering
\begin{tabular}[t]{l|c|c|c|c|c|r}
\hline
 & 1 (N=44) & 2 (N=46) & 3 (N=47) & 4 (N=48) & Total (N=185) & p value\\
\hline
\textbf{Gender} &  &  &  &  &  & 0.335\\
\hline
~~~Female & 18 (40.9\%) & 15 (32.6\%) & 16 (34.0\%) & 19 (39.6\%) & 68 (36.8\%) & \\
\hline
~~~Male & 26 (59.1\%) & 31 (67.4\%) & 28 (59.6\%) & 28 (58.3\%) & 113 (61.1\%) & \\
\hline
~~~Other & 0 (0.0\%) & 0 (0.0\%) & 3 (6.4\%) & 1 (2.1\%) & 4 (2.2\%) & \\
\hline
\textbf{age} &  &  &  &  &  & 0.981\\
\hline
~~~Mean (SD) & 22.227 (1.939) & 22.261 (1.639) & 22.234 (1.507) & 22.125 (1.632) & 22.211 (1.669) & \\
\hline
~~~Range & 20.000 - 29.000 & 19.000 - 27.000 & 20.000 - 26.000 & 20.000 - 27.000 & 19.000 - 29.000 & \\
\hline
\textbf{Ideology} &  &  &  &  &  & 0.774\\
\hline
~~~Mean (SD) & 0.455 (0.504) & 0.370 (0.488) & 0.404 (0.496) & 0.354 (0.483) & 0.395 (0.490) & \\
\hline
~~~Range & 0.000 - 1.000 & 0.000 - 1.000 & 0.000 - 1.000 & 0.000 - 1.000 & 0.000 - 1.000 & \\
\hline
\textbf{participation} &  &  &  &  &  & 0.850\\
\hline
~~~Mean (SD) & 0.955 (0.211) & 0.913 (0.285) & 0.915 (0.282) & 0.938 (0.245) & 0.930 (0.256) & \\
\hline
~~~Range & 0.000 - 1.000 & 0.000 - 1.000 & 0.000 - 1.000 & 0.000 - 1.000 & 0.000 - 1.000 & \\
\hline
\textbf{Trust} &  &  &  &  &  & 0.831\\
\hline
~~~Most people can be trusted & 43 (97.7\%) & 44 (95.7\%) & 45 (95.7\%) & 45 (93.8\%) & 177 (95.7\%) & \\
\hline
~~~People should be approached carefully & 1 (2.3\%) & 2 (4.3\%) & 2 (4.3\%) & 3 (6.2\%) & 8 (4.3\%) & \\
\hline
\textbf{Satisfaction} &  &  &  &  &  & < 0.001\\
\hline
~~~Mean (SD) & 3.409 (0.996) & 1.913 (1.029) & 3.511 (1.040) & 1.750 (0.911) & 2.632 (1.283) & \\
\hline
~~~Range & 1.000 - 5.000 & 1.000 - 4.000 & 1.000 - 5.000 & 1.000 - 4.000 & 1.000 - 5.000 & \\
\hline
\textbf{govt_provider} &  &  &  &  &  & 0.775\\
\hline
~~~Mean (SD) & 0.898 (0.147) & 0.887 (0.183) & 0.919 (0.110) & 0.890 (0.201) & 0.898 (0.164) & \\
\hline
~~~Range & 0.500 - 1.000 & 0.200 - 1.000 & 0.600 - 1.000 & 0.200 - 1.000 & 0.200 - 1.000 & \\
\hline
\textbf{gender_role} &  &  &  &  &  & 0.086\\
\hline
~~~Men & 3 (6.8\%) & 10 (21.7\%) & 4 (8.5\%) & 3 (6.2\%) & 20 (10.8\%) & \\
\hline
~~~No difference & 38 (86.4\%) & 28 (60.9\%) & 37 (78.7\%) & 38 (79.2\%) & 141 (76.2\%) & \\
\hline
~~~Women & 3 (6.8\%) & 8 (17.4\%) & 6 (12.8\%) & 7 (14.6\%) & 24 (13.0\%) & \\
\hline
\end{tabular}
\end{table}


Call:
lm_robust(formula = treatment ~ resp_gender_num + factor(Age) + 
    income + participation + ideology + gen_trust, data = data)

Standard error type:  HC2 

Coefficients:
                  Estimate Std. Error  t value Pr(>|t|) CI Lower CI Upper  DF
(Intercept)      0.8505780    0.42449  2.00378  0.04662  0.01287  1.68829 177
resp_gender_num -0.0453406    0.07847 -0.57780  0.56413 -0.20020  0.10952 177
factor(Age)2     0.0242820    0.08982  0.27034  0.78721 -0.15297  0.20154 177
factor(Age)3     0.0419615    0.14286  0.29371  0.76932 -0.23998  0.32390 177
income          -0.0005441    0.01054 -0.05162  0.95889 -0.02134  0.02026 177
participation   -0.0521943    0.15570 -0.33523  0.73785 -0.35946  0.25507 177
ideology        -0.2180420    0.19232 -1.13377  0.25842 -0.59757  0.16149 177
gen_trust       -0.0931230    0.19736 -0.47183  0.63763 -0.48261  0.29637 177

Multiple R-squared:  0.01278 ,	Adjusted R-squared:  -0.02626 
F-statistic: 0.3215 on 7 and 177 DF,  p-value: 0.9435

\begin{table}
\begin{center}
\begin{tabular}{l c}
\hline
 & Treatment -Candidate Gender (Woman=0, Man=1) \\
\hline
(Intercept)       & $0.851^{*}$ \\
                  & $(0.424)$   \\
resp\_gender\_num & $-0.045$    \\
                  & $(0.078)$   \\
income            & $-0.001$    \\
                  & $(0.011)$   \\
participation     & $-0.052$    \\
                  & $(0.156)$   \\
ideology          & $-0.218$    \\
                  & $(0.192)$   \\
gen\_trust        & $-0.093$    \\
                  & $(0.197)$   \\
\hline
R$^2$             & $0.013$     \\
Adj. R$^2$        & $-0.026$    \\
Num. obs.         & $185$       \\
RMSE              & $0.508$     \\
\hline
\multicolumn{2}{l}{\scriptsize{$^{***}p<0.001$; $^{**}p<0.01$; $^{*}p<0.05$}}
\end{tabular}
\caption{Balance table}
\label{table:coefficients}
\end{center}
\end{table}

\usepackage{booktabs}

\begin{table}
\begin{center}
\begin{tabular}{l c c c c c c c c c c c c}
\toprule
 & 0 TL & 0 TL & 200 TL & 200 TL & 400 TL & 400 TL & 600 TL & 600 TL & 800 TL & 800 TL & 1000 TL & 1000 TL \\
\midrule
(Intercept)        & $0.60^{***}$ & $0.41$   & $0.64^{***}$ & $0.69^{*}$    & $0.61^{***}$ & $1.10^{***}$ & $0.59^{***}$ & $0.47$      & $0.59^{***}$ & $0.45$        & $0.48^{***}$ & $0.74$   \\
                   & $(0.03)$     & $(0.28)$ & $(0.04)$     & $(0.36)$      & $(0.03)$     & $(0.33)$     & $(0.04)$     & $(0.37)$    & $(0.04)$     & $(0.38)$      & $(0.04)$     & $(0.48)$ \\
treatment          & $0.09^{**}$  & $0.07$   & $-0.12^{**}$ & $-0.14^{***}$ & $-0.08$      & $-0.11^{**}$ & $-0.06$      & $-0.10^{*}$ & $-0.13^{**}$ & $-0.15^{***}$ & $-0.04$      & $-0.06$  \\
                   & $(0.05)$     & $(0.05)$ & $(0.05)$     & $(0.05)$      & $(0.05)$     & $(0.05)$     & $(0.06)$     & $(0.06)$    & $(0.05)$     & $(0.06)$      & $(0.05)$     & $(0.05)$ \\
\midrule
Covariate adjusted & No           & Yes      & No           & Yes           & No           & Yes          & No           & Yes         & No           & Yes           & No           & Yes      \\
R$^2$              & $0.02$       & $0.12$   & $0.03$       & $0.16$        & $0.01$       & $0.13$       & $0.01$       & $0.13$      & $0.03$       & $0.12$        & $0.00$       & $0.13$   \\
Adj. R$^2$         & $0.02$       & $0.03$   & $0.02$       & $0.07$        & $0.01$       & $0.04$       & $0.00$       & $0.04$      & $0.02$       & $0.03$        & $-0.00$      & $0.03$   \\
Num. obs.          & $185$        & $185$    & $185$        & $185$         & $185$        & $185$        & $185$        & $185$       & $185$        & $185$         & $185$        & $185$    \\
RMSE               & $0.31$       & $0.30$   & $0.36$       & $0.35$        & $0.36$       & $0.35$       & $0.38$       & $0.37$      & $0.37$       & $0.37$        & $0.36$       & $0.35$   \\
\bottomrule
\multicolumn{13}{l}{\scriptsize{$^{***}p<0.01$; $^{**}p<0.05$; $^{*}p<0.1$}}
\end{tabular}
\caption{Linear Regression of the Probability of Voting for the LP candidate on Treatment Assignment}
\label{table:coefficients}
\end{center}
\end{table}

  1   2 
  4 181 

\usepackage{booktabs}

\begin{table}
\begin{center}
\begin{tabular}{l c c c c c c c c c c c c}
\toprule
 & 0 TL & 0 TL & 200 TL & 200 TL & 400 TL & 400 TL & 600 TL & 600 TL & 800 TL & 800 TL & 1000 TL & 1000 TL \\
\midrule
(Intercept)        & $0.60^{***}$ & $0.59^{**}$ & $0.64^{***}$ & $0.74^{*}$    & $0.62^{***}$ & $1.11^{***}$ & $0.60^{***}$ & $0.57$      & $0.59^{***}$ & $0.46$        & $0.48^{***}$ & $0.89^{*}$ \\
                   & $(0.03)$     & $(0.26)$    & $(0.04)$     & $(0.38)$      & $(0.03)$     & $(0.34)$     & $(0.04)$     & $(0.39)$    & $(0.04)$     & $(0.41)$      & $(0.04)$     & $(0.50)$   \\
treatment          & $0.10^{**}$  & $0.07$      & $-0.13^{**}$ & $-0.15^{***}$ & $-0.09$      & $-0.11^{**}$ & $-0.06$      & $-0.10^{*}$ & $-0.13^{**}$ & $-0.16^{***}$ & $-0.04$      & $-0.06$    \\
                   & $(0.04)$     & $(0.05)$    & $(0.05)$     & $(0.05)$      & $(0.05)$     & $(0.05)$     & $(0.06)$     & $(0.06)$    & $(0.05)$     & $(0.06)$      & $(0.05)$     & $(0.05)$   \\
\midrule
Covariate adjusted & No           & Yes         & No           & Yes           & No           & Yes          & No           & Yes         & No           & Yes           & No           & Yes        \\
R$^2$              & $0.03$       & $0.12$      & $0.03$       & $0.15$        & $0.01$       & $0.12$       & $0.01$       & $0.12$      & $0.03$       & $0.12$        & $0.00$       & $0.13$     \\
Adj. R$^2$         & $0.02$       & $0.02$      & $0.03$       & $0.06$        & $0.01$       & $0.02$       & $0.00$       & $0.03$      & $0.03$       & $0.02$        & $-0.00$      & $0.03$     \\
Num. obs.          & $181$        & $181$       & $181$        & $181$         & $181$        & $181$        & $181$        & $181$       & $181$        & $181$         & $181$        & $181$      \\
RMSE               & $0.30$       & $0.30$      & $0.36$       & $0.35$        & $0.36$       & $0.35$       & $0.38$       & $0.38$      & $0.37$       & $0.37$        & $0.36$       & $0.35$     \\
\bottomrule
\multicolumn{13}{l}{\scriptsize{$^{***}p<0.01$; $^{**}p<0.05$; $^{*}p<0.1$}}
\end{tabular}
\caption{Linear Regression of the Probability of Voting for the LP candidate on Treatment Assignment excluding respondents experienced any type of trouble listening the experimental stimuli}
\label{table:coefficients}
\end{center}
\end{table}

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\usepackage{booktabs}

\begin{table}
\begin{center}
\begin{tabular}{l c c c c c c}
\toprule
 & 0 TL & 200 TL & 400 TL & 600 TL & 800 TL & 1000 TL \\
\midrule
(Intercept)        & $0.41$   & $0.76^{**}$   & $1.13^{***}$ & $0.55$   & $0.50$       & $0.67$   \\
                   & $(0.28)$ & $(0.36)$      & $(0.35)$     & $(0.36)$ & $(0.41)$     & $(0.47)$ \\
treatment          & $0.08$   & $-0.14^{***}$ & $-0.09^{*}$  & $-0.09$  & $-0.14^{**}$ & $-0.06$  \\
                   & $(0.05)$ & $(0.05)$      & $(0.05)$     & $(0.06)$ & $(0.06)$     & $(0.06)$ \\
\midrule
Covariate adjusted & Yes      & Yes           & Yes          & Yes      & Yes          & Yes      \\
R$^2$              & $0.13$   & $0.18$        & $0.14$       & $0.16$   & $0.14$       & $0.16$   \\
Adj. R$^2$         & $0.02$   & $0.07$        & $0.02$       & $0.05$   & $0.02$       & $0.05$   \\
Num. obs.          & $179$    & $179$         & $179$        & $179$    & $179$        & $179$    \\
RMSE               & $0.30$   & $0.35$        & $0.35$       & $0.37$   & $0.37$       & $0.35$   \\
\bottomrule
\multicolumn{7}{l}{\scriptsize{$^{***}p<0.01$; $^{**}p<0.05$; $^{*}p<0.1$}}
\end{tabular}
\caption{Linear Regression of the Probability of Voting for the LP candidate on Treatment Assignment}
\label{table:coefficients}
\end{center}
\end{table}
[1] 0.8736842

  0   1 
285 285 

	One Sample t-test

data:  data_val_long$rating
t = 62.734, df = 569, p-value < 0.00000000000000022
alternative hypothesis: true mean is greater than 0
95 percent confidence interval:
 0.8507394       Inf
sample estimates:
mean of x 
0.8736842 


	Paired t-test

data:  rating by candidate_gender
t = 1.1803, df = 284, p-value = 0.2388
alternative hypothesis: true mean difference is not equal to 0
95 percent confidence interval:
 -0.01873970  0.07488005
sample estimates:
mean difference 
     0.02807018 

